Evidence map›Paper›PMID 29105913›Full record

ReviewBJOG : an international journal of obstetrics and gynaecology2018

A step-wise approach to developing indicators to compare the performance of maternity units using hospital administrative data.

R S Geary, H E Knight, F E Carroll, I Gurol-Urganci, E Morris, D A Cromwell, J H van der Meulen

Abstract readReview
In one paragraph

Review in BJOG : an international journal of obstetrics and gynaecology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Observational
  9. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

R S GearyDepartment of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK.
H E KnightDepartment of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK.
F E CarrollRoyal College of Obstetricians and Gynaecologists, Lindsay Stewart Centre for Audit and Clinical Informatics, London, UK.
I Gurol-UrganciDepartment of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK.
E MorrisRoyal College of Obstetricians and Gynaecologists, Lindsay Stewart Centre for Audit and Clinical Informatics, London, UK.
D A CromwellDepartment of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK.
J H van der MeulenDepartment of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hospital administrative data are attractive for comparing performance of maternity units because of their often large sample sizes, lack of selection bias and the relatively low costs of accessing these data compared with conducting primary data collection. However, using administrative data to develop indicators can also present challenges including varying data quality, the limited detail on clinical risk factors and a lack of structural and user experience measures. This review illustrates how to develop performance indicators for maternity units using hospital administrative data, including methods to address the challenges that administrative data pose. TWEETABLE ABSTRACT: How to develop maternity indicators from administrative data.

Indexed as

Delivery RoomsFemaleHumansMaternal Health ServicesPregnancyQuality Assurance, Health CareQuality Indicators, Health CareAdministrative datahospital episode statisticsmaternity statisticsperformance indicators

Identifiers

PMID29105913
PMCPMC6001534

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.